해양과학 데이터저장소 JOISS는 FAIR한가?

송태윤,이지윤,김우람,박소예나,노태근 (사)지오에이아이데이터학회 2022 GEO DATA Vol.4 No.2

As the global open science movement has recently proven its effectiveness in responding to the coronapandemic, research on disciplinary or institutional data repositories and establishing service platforms for theopen and sharing research data are also active in Korea. The purpose of the research data repository is not tomanage data per se but to discover and innovate knowledge and to integrate and reuse subsequent data andknowledge. Therefore, recent repository-related studies emphasize implementing the FAIR principle in thiscollaborative process, from observation to data documentation, data combination, quality control, and datapublication. In particular, high-level data interoperability through the FAIR implementation of the repository is송태윤 · 이지윤 · 김우람 · 박소예나 · 노태근GEO DATA [4.2]: 47–56 (2022) 48essential for ocean observation that requires multidisciplinary collaborative research. In Korea, ocean observatoryorganizations have repositories, including the ocean science data repository, JOISS; however, no studies evaluatethe establishment and operation of data repositories in the FAIR principle. Therefore, this study aims to examinethe construction process and data management status of the JOISS repository and the main functions andservices of the web platform in terms of the data lifecycle and evaluate The FAIR principle of Open Science worksin such an operating system and its limitations. The study provides implications for the improvement direction ofdata management and services of domestic marine repositories, including the JOISS, in an environment where thediversity and volume of data are rapidly increasing along with the evolution of ocean observation

다목적실용위성 광학영상을 활용한 AI 학습용 도로 검출 데이터셋

이훈희,오한 (사)지오에이아이데이터학회 2022 GEO DATA Vol.4 No.1

인공위성의 광학영상에 보이는 도로의 형태 및 종류 정보는 수치적 지도 제작 및 도로 변화 감시에 유용하다. 다목적실용위성 3호와 3A호에 탑재된 광학 카메라로부터 수집되는 광학영상 데이터를 가공하고 구조화하면 도로 검출 알고리즘의 개발과 이러한 분석 도구를 이용한 도로 정보 산출 작업을 가속화할 수 있다. 특히, 딥러닝(Deep Learning) 학습 기술을 적용할 수 있도록 준비된 AI (Artificial Intelligence)용 학습 데이터셋으로구축되면 컴퓨터 과학 분야의 최신 인공지능 기술을 위성영상 기반 도로 검출 분야에 스핀오프(Spin-off)하여폭넓은 분석을 시도할 수 있다. 한국항공우주연구원은 국내 여러 업체와 함께 위성 광학영상을 이용하여 AI 학습용 도로 영상 데이터셋을 구축하였으며 본 논문에서는 이 데이터셋의 활용 예시와 함께 데이터셋의 종류, 규모 등에 관하여 설명한다. 구축된 데이터는 aihub.or.kr 웹사이트를 통해 이용할 수 있다.

온실가스 지중저장 적지 탐사 데이터 구축: 지질단면도 데이터를 중심으로

고보균,Park, Sungjae,이사로 (사)지오에이아이데이터학회 2023 GEO DATA Vol.5 No.3

In this study, the most basic data, underground geological structure data, that is, geological cross-section data, were established to select a candidate site for underground storage of greenhouse gases based on AI. As a target area, the Gyeongsang Basin, where a large amount of sedimentary rocks are distributed, was selected as the greenhouse gas can be stored most effectively in sedimentary rocks. To this end, the acquisition and edit step, the refinement step, and the labeling step were carried out in the order of raw data collection, source data and labeling data construction to construct the geological cross-section data. This data can be downloaded through the AI hub site (https://aihub.or.kr/aihubdata/data/view.do?curr Menu=115&topMenu=100&aihubDataSe=realm&dataSetSn=71390) operated by the Korea Institute for Intelligent Information Society Promotion.

다목적실용위성 5호 GNSS 전파 엄폐 데이터 운영

정옥철,성재동,이명신,정대원 (사)지오에이아이데이터학회 2022 GEO DATA Vol.4 No.3

The Korea Aerospace Research Institute launched KOMPSAT-5 on August 22, 2013, and has been operating for 10 years. KOMPSAT-5 has SAR (Synthetic Aperture Radar) for earth observation missions, and collects data necessary for earth atmosphere analysis through GNSS RO (Radio Occultation) receivers. RO data can be used for numerical weather forecast model based on temperature, pressure, and humidity by calculating the vertical distribution of atmospheric information. As a part of the Korea-US science and technology cooperation, KARI has been providing RO data of KOMPSAT-5 to the United States NOAA (National Oceanic and Atmospheric Administration) in near-real time since 2018. To this end, KARI receives telemetry data from the satellite about 12 times a day using 3 ground stations from Daejeon, Alaska in the U.S., and Sodankyla in Finland. The pre-processed data is being provided to both the UCAR (University Corporation for Atmospheric Research) in the U.S. and the KASI (Korea Astronomy and Space Science Institute). In this paper, radio occlusion data of KOMPSAT-5 is introduced, and system configuration, operation concepts for providing near-real time data and its application are also presented. 한국항공우주연구원은 2013년 8월 22일 다목적실용위성 5호를 발사하여 10년차 운영을 수행하고 있다. 다목적실용위성 5호는 SAR (Synthetic Aperture Radar)를 이용하여 지구관측 임무를 수행하면서 동시에 GNSS (Global Navigation Satellite System) 전파 엄폐(Radio Occultation, RO) 수신기를 통해 지구대기 분석에 필요한 데이터를 수집하고 있다. 전파 엄폐 데이터는 대기정보의 연직분포 산출을 통해 온도, 압력, 습도 등을 파악할 수 있어 기상예보를 위한 수치모델에 활용 가능하다. 한국항공우주연구원은 한-미 과학기술 협력의 일환으로 2018년부터 미국 국립해양대기청(National Oceanic and Atmospheric Administration, NOAA)에 다목적실용위성 5호의 대기 엄폐 데이터를 준-실시간으로 제공하고 있다. 이를 위해 한국항공우주연구원에서는 대전 지상국, 미국 알래스카(Alaska) 지상국, 핀란드 소단킬라(Sodankyla) 지상국을 이용하여 하루 약 12회 위성으로부터 텔레메트리 데이터를 수신하여 전처리 후 전파 엄폐 데이터를 미국 기상연구대학연합(University Corporation for Atmospheric Research, UCAR)과 한국천문연구원에 동시에 제공하고 있다. 본 논문에서는 다목적실용위성 5호의 전파 엄폐 데이터를 소개하고, 준-실시간 자료 제공을 위한 시스템 구성 및 운영개념, 그리고 데이터 활용 사례를 제시하였다.

로드킬 정보시스템으로 수집된 고양이 로드킬 발생 현황 연구

허수안,Kim Il Ryong,김세희,이한비,송의근 (사)지오에이아이데이터학회 2023 GEO DATA Vol.5 No.4

The IntegrateThe incidence of roadkill and habitat fragmentation caused by human development and road networks is on the rise. Cats primarily consume artificial food and engage in hunting near urban areas. Their numbers have an impact on the ecosystem, and cat roadkill incidents are also prevalent. In South Korea, roadkill observations are conducted by the road management agency and the Korea Roadkill Observation System. Over a 3-year period, the number of cat roadkill incidents resulted in 19,973 recorded cases, and the highest rate was in Busan Metropolitan City. Cat roadkill incidents were most prevalent during October and November. Also When analyzed at the local government level, Dangjin-si, Yangpyeong-gun, and Busan Metropolitan City exhibited the highest concentrations. This research offers essential insights for managing the cat population and mitigating cat roadkill occurrences.d Dataset of Cat (Felis catus) Roadkill by Korea Roadkill Observation System

한국 수산시장에서 판매되는 뱀장어속(Anguilla) 어류의 진위판별법 개발 및 유통실태

장요순 (사)지오에이아이데이터학회 2022 GEO DATA Vol.4 No.1

This study was carried out to identify the mislabeling of Japanese eel (Anguilla japonica) sold on the fish marketsin Korea and to develop a method for determining the authenticity of fresh and trimmed eels. Between January andDecember 2018, 31 test samples were collected from restaurants and fish markets in Seoul, South Korea, and the collectedsamples were analyzed. The results showed that over two-thirds of the samples tested were mislabeled. Molecularidentification of 31 test samples revealed that 10 Anguilla japonica, 9 Anguilla Anguilla, 2 Anguilla rostrate, 1 Anguillamarmorata, 7 Ophichthus remiger, 1 Brachysomophis crocodilinus, and 1 Conger myriaster. We have developed the NdeⅠPCR-RFLP assay for determining the authentication of fresh and trimmed eels sold on the fish markets in Korea, andthis assay enables rapidly and accurately identify the genus Anguilla. 본 연구는 우리나라 수산시장에서 유통되는 뱀장어(Japanese eel, Anguilla japonica)의 허위정보 표시 실태를파악하고, 뱀장어 선어 및 손질·가공품의 진위판별법을 개발하기 위하여 수행되었다. 2018년 1월부터 12월까지서울지역의 장어 전문식당과 수산시장에서 조사샘플 31개를 수집하여 분석한 결과, 67.74%에 해당하는 21개장어샘플이 허위정보 표시로 유통되고 있음을 확인하였다. 31개의 조사샘플을 분자동정한 결과, 극동산뱀장어(Anguilla japonica) 10개, 유럽산 뱀장어(Anguilla Anguilla) 9개, 미국산 뱀장어(Anguilla rostrate) 2개,무태장어(Anguilla marmorata) 1개, Ophichthus remiger 7개, Brachysomophis crocodilinus 1개, 붕장어(Conger myriaster)1개로 확인되었다. 이와 같은 뱀장어 오표시 유통 실태 조사결과를 근거로 본 연구에서는 선어 또는손질가공품으로 판매되는 뱀장어가 Anguilla 속 어류에 속하는지 여부를 빠르게 판별할 수 있는 NdeⅠ PCR-RFLP분석법을 개발하였다.

고창군의 비오톱 유형도 및 등급평가도 작성에 관한 연구

김정철,유창훈,김동욱,오우석 (사)지오에이아이데이터학회 2023 GEO DATA Vol.5 No.4

Gochang-gun, situated in Korea, has achieved the distinction of being the second city in the country to have all three UNESCO-designated natural environmentrelated World Heritage Sites, following in the footsteps of Jeju Island. UNESCO has conferred upon Gochang-gun the prestigious designations of a biosphere reserve, World Natural Heritage (Gochang-Buan mudflat), and World Geopark (Jeonbuk West Coast Geopark). Notably, the entire administrative district has been designated as a UNESCO Biosphere Reserve, signifying its role as a meticulously preserved region of outstanding natural beauty and ecological significance. Within this UNESCO Biosphere Reserve, the core areas encompass remarkable features, including the Gochang-Buan Mudflat, Ungok Wetland, Dolmen World Cultural Heritage sites, Seonunsan Provincial Park, and Dongrim Reservoir. In pursuit of a comprehensive ecological map of Gochang-gun, the National Institute of Ecology (NIE) conducted an extensive two-year ecological survey and biotope survey from 2021 to 2022. Ecological spatial data was meticulously compiled based on the results of these surveys. The resulting Biotope map provides detailed information on various attributes, encompassing Biotope types, Biotope grades, land cover status, land use status, and topographic details. This dataset is formally registered and rigorously managed, employing the Digital Object Identifier (DOI) system. The primary aim of this paper is to provide a comprehensive introduction to each attribute of the Gochang-gun Biotope map, which represents a detailed collection of spatial ecology data for the region. The intent is to make this data readily accessible for future research and studies, thereby advancing our understanding of Gochang-gun’s distinctive ecological and cultural heritage.

완도 붉가시나무림 5년간(2017-2021년)의 나비 다양성에 대한 정량적 연구

이상훈,안나현 (사)지오에이아이데이터학회 2023 GEO DATA Vol.5 No.2

This study presents the long-term quantitative data on butterflies in Wando Arboretum, which represents the only warm-temperate forest located in the southernmost part of South Korea. This arboretum has significant academic value as approximately 770 species of rare woody plants or herbs, such as the Japanese evergreen oak (Quercus acuta), found in warm temperate zones grow under natural conditions here. In this project, the butterflies in this region were studied due to their sensitivity to temperature changes. The study was conducted from March-April to October-November over 5 years (2017-2021) in the region dominated by Japanese evergreen oak. We found 1,743 individuals of 47 butterfly species belonging to five families. The acquired butterfly data could serve as a reference for the further development of a network-oriented database for assessing temporal climate changes.

댐 일유입량 예측을 위한 데이터 전처리 방법에 따른 머신러닝 및 딥러닝 모델 적용의 비교연구

조영식,정관수 (사)지오에이아이데이터학회 2023 GEO DATA Vol.5 No.2

In this study, we employed representative machine learning (ML) and deep learning (DL) models previously utilized in the fields of rainfall and runoff analysis in the water resources sector. We not only performed hyperparameter tuning of the models but also considered the characteristics of the model and the combination and preprocessing (such as lag-time and moving average) of meteorological and hydrological data. We then compared and evaluated the performance of the models according to various scenarios of data characteristics and ML & DL model combinations for predicting daily water inflow. To accomplish this, we utilized meteorological and hydrological data collected from 1974 to 2021 in the Soyang River Dam Basin to examine 1) precipitation, 2) inflow, and 3) meteorological data as primary independent variables. We then employed a total of 36 scenario combinations as input data for ML & DL, applying a) lag-time, b) moving average, and c) component separation conditions for inflow. To identify the most suitable data combination characteristics and ML & DL models for predicting daily inflow, we compared and evaluated 10 different ML & DL models: 1) Linear Regression, 2) Lasso, 3) Ridge, 4) Support Vector Regression, 5) Random Forest (RF), 6) Light Gradient Boosting Model, 7) XGBoost for ML, and 8) Long Short-Term Memory (LSTM) models, 9) Temporal Convolutional Network (TCN), and 10) LSTM-TCN for DL.

홍수와 산사태 취약성도 작성을 위한 전 세계 지공간데이터

이사로,Rezaie Fatemeh (사)지오에이아이데이터학회 2023 GEO DATA Vol.5 No.4

Susceptibility mapping is an important component of natural hazard risk assessment and management. Susceptibility maps for floods and landslides, which are particularly damaging to human life and property, can provide a comprehensive understanding of risk areas and factors related to flood and landslide susceptibility. To create a global flood and landslide susceptibility map, global geospatial data for 37,984 landslide and 6,682 flood locations, as well as 11 selected environmental factors were used to construct a geographic information system database. The 11 environmental factors found to influence flood and landslide occurrence were rainfall, slope, terrain position index, plane curvature, terrain wetness index, distance from rivers, land use, soil texture, soil moisture, geology, and temperature. These data were then used directly to create a global flood and landslide susceptibility map.